Deliverables News alert system The ALERT project aimed to associate state-of-the-art speech recognition with audio and video segmentation and automatic topic indexing to develop an automatic media-monitoring demonstrator and evaluate it in the context of real world applications. The targeted languages were French, German and Portuguese. This is a complete ALERT system that is capable of continuously monitoring TV channels, and searching inside their news programs for stories that match the profile of a given user. The system may be tuned to automatically detect the start and end of a broadcast news program. When the program is detected the system automatically records, transcribes, indexes summarizes and stores the program. After that, the system then searches in all the user profiles for the ones that fit into the detected topics. If any topic matches the user preferences, an email is send to that user indicating the occurrence and location of one or more stories about the selected topics. This alert message enables a user to follow the links to the video clips referring to the selected stories. More information on ALERT: http://alert.uni-duisburg.de/start.html Audiovisual media monitoring prototype The ALERT project demonstrated that by associating state-of-the-art speech recognition with audio and video segmentation and automatic topic detection, an automatic media monitoring demonstration system can be developed that detects topics in large amounts of multimedia data and alerts those users about the detection of this information that it is relevant for. The ALERT demonstrator has been developed for the three languages French, German and Portuguese and is capable of processing and indexing multimedia content (radio or TV broadcast or internet audio/video) with a strong focus on news and information programs. The developed prototype is software running on a PC under Linux. This software transcribe into text broadcast news audio files in French and American English. The main components of the system are an audio partitioner, a speech recogniser and a topic detector. More information on ALERT: http://alert.uni-duisburg.de/start.html Multilingual audio indexation system The ALERT project aimed to associate state-of-the-art speech recognition with audio and video segmentation and automatic topic indexing to develop an automatic media monitoring demonstrator and evaluate it in the context of real world applications. The targeted languages were French, German and Portuguese. The multilingual indexation system combines state-of-the-art automatic transcription capabilities for indexation of broadcast data in four languages: American English, French, German and Portuguese. The main components of the system are the audio partitioner and the speech recogniser, and the topic detector. All are based on statistical modelling techniques. Data partitioning is based on a language independent iterative maximum likelihood segmentation/clustering procedure using Gaussian mixture models and agglomerative clustering. The speech recogniser makes use of continuous density HMMs with Gaussian mixture for acoustic modelling and 4-gram statistics estimated on large text corpora. Word recognition is performed in multiple passes, where initial hypotheses are used for cluster-based acoustic model adaptation to improve word graph generation. The spoken document retrieval demonstrator returns audio and/or video segments matching a typed natural language query. The extracts are selected from automatically derived transcriptions of shows. The demonstrator also displays the result of the partitioning process (speaker and acoustic condition labels), and the speech transcriptions synchronized with the audio signal. More information on ALERT: http://alert.uni-duisburg.de/start.html Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
